Data Science

Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.

Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies. Mining large amounts of structured and unstructured data to identify patterns can help an organization rein in costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage.

The data science field employs mathematics, statistics and computer science disciplines, and incorporates techniques like machine learning, cluster analysis, data mining and visualization.

Data science is a "concept to unify statistics, data analysis and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, in particular from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization.

Turing award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.

When Harvard Business Review called it "The Sexiest Job of the 21st Century" the term became a buzzword, and is now often applied to business analytics, or even arbitrary use of data, or used as a sexed-up term for statistics. While many university programs now offer a data science degree, there exists no consensus on a definition or curriculum contents. Because of the current popularity of this term, there are many "advocacy efforts" surrounding it.

Benefits of data science

The main advantage of enlisting data science in an organization is the empowerment and facilitation of decision-making. Organizations with data scientists can factor in quantifiable, data-based evidence into their business decisions. These data-driven decisions can ultimately lead to increased profitability and improved operational efficiency, business performance and workflows. In customer-facing organizations, data science helps identify and refine target audiences. Data science can also assist recruitment: Internal processing of applications and data-driven aptitude tests and games can help an organization's human resources team make quicker and more accurate selections during the hiring process.

The specific benefits of data science vary depending on the company's goal and the industry. Sales and marketing departments, for example, can mine customer data to improve conversion rates or create one-to-one marketing campaigns. Banking institutions are mining data to enhance fraud detection. Streaming services like Netflix mine data to determine what its users are interested in, and use that data to determine what TV shows or films to produce. Data-based algorithms are also used at Netflix to create personalized recommendations based on a user's viewing history. Shipment companies like DHL, FedEx and UPS use data science to find the best delivery routes and times, as well as the best modes of transport for their shipments.

A day in the life of a

data scientist.

Data science is still an emerging field within the enterprise because the identification and analysis of vast amounts of unstructured data can prove too complex, expensive and time-consuming for companies.